U.S. patent number 9,186,114 [Application Number 13/628,498] was granted by the patent office on 2015-11-17 for method for producing a noise-reduced ct image data record, computer system, and ct system.
This patent grant is currently assigned to Siemens Aktiengesellschaft. The grantee listed for this patent is Siemens Aktiengesellschaft. Invention is credited to Thomas Flohr, Bernhard Krau.beta., Rainer Raupach, Bernhard Schmidt.
United States Patent |
9,186,114 |
Flohr , et al. |
November 17, 2015 |
Method for producing a noise-reduced CT image data record, computer
system, and CT system
Abstract
A method is disclosed for producing a noise-reduced CT image
data record by frequency band breakdown, a computer system for
carrying out the method, and a CT system (1) with such a computer
system. In an embodiment of the method, several linear-combined
mixed image data records .times. ##EQU00001## are produced from
several simultaneously-recorded energy spectrum-specific CT image
data records (X.sub.i); a frequency band breakdown of the mixed
image data records (M.sub.m) takes place into a first lowest
frequency band (F.sub.0) and several higher frequency bands; and a
result image data record .times..function. ##EQU00002## is
calculated, wherein each mixed image data record (M.sub.m) is
multiplied with precisely one filter and with a location-dependent
function (g.sub.j,m(r)) and is thereby totaled, and wherein
g.sub.0,0(r)=1.
Inventors: |
Flohr; Thomas (Uehlfeld,
DE), Krau.beta.; Bernhard (Burgthann, DE),
Raupach; Rainer (Heroldsbach, DE), Schmidt;
Bernhard (Furth, DE) |
Applicant: |
Name |
City |
State |
Country |
Type |
Siemens Aktiengesellschaft |
Munich |
N/A |
DE |
|
|
Assignee: |
Siemens Aktiengesellschaft
(Munich, DE)
|
Family
ID: |
47878522 |
Appl.
No.: |
13/628,498 |
Filed: |
September 27, 2012 |
Prior Publication Data
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|
|
Document
Identifier |
Publication Date |
|
US 20130083989 A1 |
Apr 4, 2013 |
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Foreign Application Priority Data
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Sep 29, 2011 [DE] |
|
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10 2011 083 727 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B
6/03 (20130101); A61B 6/4014 (20130101); A61B
6/482 (20130101); A61B 6/032 (20130101); A61B
6/541 (20130101) |
Current International
Class: |
G06K
9/00 (20060101); A61B 6/03 (20060101); A61B
6/00 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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101023875 |
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Aug 2007 |
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CN |
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101175440 |
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Jun 2009 |
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CN |
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102005049586 |
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Apr 2007 |
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DE |
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102008051043 |
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Feb 2010 |
|
DE |
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102008045633 |
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Mar 2010 |
|
DE |
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102009015772 |
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Aug 2010 |
|
DE |
|
Primary Examiner: Bali; Vikkram
Attorney, Agent or Firm: Harness, Dickey & Pierce
Claims
What is claimed is:
1. A method for producing a result image data record, the method
comprising: simultaneously recording a plurality of energy
spectrum-specific CT image data records (X.sub.i) with different
X-ray energy spectra (R.sub.i) or received from a plurality of
simultaneously-recorded energy spectrum-specific CT image data
records (X.sub.i) with different X-ray energy spectra (R.sub.i);
calculating a plurality of linear mixed image data records .times.
##EQU00030## mixed from the energy spectrum-specific CT image data
records (X.sub.i); breaking down, via frequency band breakdown, the
mixed image data records (M.sub.m) into a first relatively lowest
frequency band produced with a low-pass filter (F.sub.0) and a
plurality of relatively higher frequency bands produced by other
filters (F.sub.j), wherein all the other filters (F.sub.j,
j.noteq.0) block a frequency zero and wherein a sum over all the
filters for all frequencies (f) is standardized .times..function.
##EQU00031## and calculating the result image data record
.times..function. ##EQU00032## in which each mixed image data
record (M.sub.m) is multiplied by precisely one of the filters and
by one location-dependent function (g.sub.j,m(r)) and is totaled,
wherein g.sub.0,0(r)=1.
2. The method of claim 1, wherein the location-dependent function
(g.sub.j,m(r)) is arranged such that local areas of the skin
surface exhibit a constant value which is different from inner
regions of the patient.
3. The method of claim 1, wherein the location-dependent function
(g.sub.j,m(r)) is determined locally from a statistical evaluation
of the surroundings of each voxel (V(r)) at the location (r).
4. The method of claim 3, wherein the statistical evaluation
includes: selecting a CT image data record (X.sub.1); calculating
regression coefficients (k.sub.i=gradient of the regression lines)
from the CT image data record (X.sub.1), moving over adjacent
voxels (V(r.+-..DELTA.r)) of every voxel considered (V(r)), to the
remaining CT image data records (X.sub.i), which indicate the
mutual dependency of the CT values of the adjacent voxel
(V(r.+-..DELTA.r)) in each case of the CT image data records
(X.sub.i) to the selected CT image data record (X.sub.1),
determining a location-dependent scaling function
.function..times..times..times..times. ##EQU00033## determining,
from the location-dependent scaling function, the
location-dependent function (g.sub.j,m(r)=w.sub.j,m(r)h.sub.m(r)),
wherein .times. ##EQU00034## is for all j; and determining the
result image data record .times..function. ##EQU00035## as a
totaling of a product from the location-dependent function with the
filters and the mixed images.
5. The method of claim 1, wherein the location-dependent function
(g.sub.j,m(r)) is determined by a classification on the basis of
the local CT values.
6. The method of claim 1, wherein the location-dependent function
(g.sub.j,m(r)) is determined by a classification of
locally-determined materials.
7. The method of claim 1, wherein the local materials are
determined by a material breakdown of the CT image data records
(X.sub.i) into at least two materials.
8. The method of claim 1, wherein the energy spectrum-specific CT
image data records (X.sub.i) are two-dimensional section image data
records.
9. The method of claim 1, wherein the energy spectrum-specific CT
image data records (X.sub.i) are three dimensional volume image
data records.
10. The method of claim 1, wherein, as energy-specific CT image
data records (X.sub.i), two CT image data records (X.sub.i) of a
dual-energy CT scan are used.
11. The method of claim 1, wherein the respective CT image data
records (X.sub.i) derive from or correspond to a scanning with a
mono-energetic X-ray spectrum.
12. The method of claim 1, wherein the respective CT image data
records (X.sub.i) correspond to a scanning with a mono-energetic
X-ray spectrum.
13. A computer system, comprising: a memory, configured to store a
computer program which is to be executed during operation of the
computer system, the computer program carrying out the method of
claim 1 when executed.
14. A CT system for producing several linear mixed image data
records .times. ##EQU00036## mixed from the energy
spectrum-specific CT image data records (X.sub.i), comprising the
computer system of claim 13.
15. The method of claim 8, wherein, as energy-specific CT image
data records (X.sub.i), two CT image data records (X.sub.i) of a
dual-energy CT scan are used.
16. The method of claim 9, wherein, as energy-specific CT image
data records (X.sub.i), two CT image data records (X.sub.i) of a
dual-energy CT scan are used.
17. A non-transitory computer readable medium including computer
program product, the computer program product comprising
instructions, which when executed by a processor, cause the
processor to perform the function of claim 1.
Description
PRIORITY STATEMENT
The present application hereby claims priority under 35 U.S.C.
.sctn.119 to German patent application number DE 10 2011 083 727.2
filed Sep. 29, 2011, the entire contents of which are hereby
incorporated herein by reference.
FIELD
At least one embodiment of the invention generally relates to a
method for producing a noise-reduced CT image data record by
frequency band breakdown, a computer system for carrying out
embodiments of the method, and/or a CT system with such a computer
system.
BACKGROUND
It is generally known that, with the aid of multi-energy CT systems
it is possible to record simultaneously CT image data records of an
object with different X-ray spectra. As a rule, the attempt is made
to calculate from these CT image data records a single image with
the desired information, such as a CT image which corresponds to a
mono-energy spectrum, or only represents the contrast agent
distribution in the scanned object. To this end, a linear-mixed
image
.times. ##EQU00003## can be produced, wherein X.sub.i designates
the den CT image data record for the i-th X-ray spectrum, the
coefficients are selected such as to achieve a special image
impression, and m=0. Unfortunately, the noise in such linear
combinations can increase substantially in comparison with a
noise-optimized mixed image.
In the prior art there are many possibilities known for reducing
the noise of the mixed images which are produced. For example, a
linear filter in the form of a low-pass filter can be used,
wherein, however, the spatial resolution is sharply reduced. As an
alternative, non-linear filters are used, but, with complex
structures in the object represented, the problem arises of
distinguishing fine structures from the noise.
SUMMARY
At least one embodiment of the invention provides an improved
method for producing a noise-reduced CT image data record from
several CT image data records, recorded with different X-ray energy
spectra.
Advantageous developments of the invention form the subject matter
of the subordinated claims.
A method is proposed, in at least one embodiment, for producing a
noise-reduced CT mixed image data record as a result image data
record which comprises the method steps indicated in the following
enumeration:
Simultaneous recording of several energy spectrum-specific CT image
data records X.sub.i with different X-ray energy spectra R.sub.i or
received from several simultaneously recorded energy
spectrum-specific CT image data records X.sub.i with different
X-ray energy spectra R.sub.i,
Calculation of several linear-mixed mixed image data records
.times. ##EQU00004## from the energy spectrum-specific CT image
data records X.sub.i
Frequency band breakdown of the mixed image data records M.sub.m
into a first lowest frequency band, produced with a low-pass filter
F.sub.0, and several higher frequency bands, produced by other
filters F.sub.j, wherein all the other filters F.sub.j block the
frequency zero and the sum
.times..function. ##EQU00005## over all the filters is standardized
for all frequencies f, and
Calculation of a result image data record
.times..function. ##EQU00006## in that each mixed image data record
M.sub.m is multiplied by precisely one filter and with a
location-dependent function g.sub.j,m(r) and thereby totaled,
wherein g.sub.0,0(r)=13.
As well as the method according to embodiments of the invention,
the inventors also propose a computer system, which comprises a
memory for the storing of a computer program to be carried out
during operation, wherein the computer program carries out the
method steps in accordance with one of the preceding method
embodiments.
In addition to this, an embodiment of the invention also includes a
CT system for the production of several linear mixed image data
records, mixed from the energy spectrum-specific CT image data
records, with a computer system such as described heretofore.
BRIEF DESCRIPTION OF THE DRAWINGS
The invention is described hereinafter in greater detail on the
basis of example embodiments and with the aid of the Figures,
wherein only those features are represented which are necessary for
the understanding of the invention. The following reference numbers
are used: 1: Dual-source/Dual-energy CT system; 2: First X-ray
tubes; 3: First detector; 4: Second X-ray tubes; 5: Second
detector; 6: Gantry housing; 7: Patient; 8: Examination couch: 9:
System axis; 10: Control and calculation unit; 11: Contrast medium
applicator; 12: Control and data line; 13: ECG lead; 14: Memory;
15: Computer programs; E: Result image; F0: Low-pass filter; F1:
High-pass filter; Fi: Filter operations; M0: Image; M1: Mixed
image; Mm: Mixed image data records; Ri: X-ray energy spectrum; S1:
Determination of C-image data records; S2: Formation of mixed image
data records; S3: Breakdown of the mixed image data records into
different frequency bands; S4: Determination of the
location-dependent function; S5: Calculation of the mixed image;
V(r): Voxel; V(r.+-..DELTA.r): Voxels in the adjacent region with
maximum distance interval .DELTA.r.
Specifically, the following are shown:
FIG. 1: Dual-source/Dual-energy CT-System;
FIG. 2: Two diagrammatically-represented CT image data records for
the correlation consideration;
FIG. 3: Diagrammatic representation of the method according to an
embodiment of the invention;
FIG. 4: Alternative representation of the method sequence.
DETAILED DESCRIPTION OF THE EXAMPLE EMBODIMENTS
Various example embodiments will now be described more fully with
reference to the accompanying drawings in which only some example
embodiments are shown. Specific structural and functional details
disclosed herein are merely representative for purposes of
describing example embodiments. The present invention, however, may
be embodied in many alternate forms and should not be construed as
limited to only the example embodiments set forth herein.
Accordingly, while example embodiments of the invention are capable
of various modifications and alternative forms, embodiments thereof
are shown by way of example in the drawings and will herein be
described in detail. It should be understood, however, that there
is no intent to limit example embodiments of the present invention
to the particular forms disclosed. On the contrary, example
embodiments are to cover all modifications, equivalents, and
alternatives falling within the scope of the invention. Like
numbers refer to like elements throughout the description of the
figures.
Before discussing example embodiments in more detail, it is noted
that some example embodiments are described as processes or methods
depicted as flowcharts. Although the flowcharts describe the
operations as sequential processes, many of the operations may be
performed in parallel, concurrently or simultaneously. In addition,
the order of operations may be re-arranged. The processes may be
terminated when their operations are completed, but may also have
additional steps not included in the figure. The processes may
correspond to methods, functions, procedures, subroutines,
subprograms, etc.
Methods discussed below, some of which are illustrated by the flow
charts, may be implemented by hardware, software, firmware,
middleware, microcode, hardware description languages, or any
combination thereof. When implemented in software, firmware,
middleware or microcode, the program code or code segments to
perform the necessary tasks will be stored in a machine or computer
readable medium such as a storage medium or non-transitory computer
readable medium. A processor(s) will perform the necessary
tasks.
Specific structural and functional details disclosed herein are
merely representative for purposes of describing example
embodiments of the present invention. This invention may, however,
be embodied in many alternate forms and should not be construed as
limited to only the embodiments set forth herein.
It will be understood that, although the terms first, second, etc.
may be used herein to describe various elements, these elements
should not be limited by these terms. These terms are only used to
distinguish one element from another. For example, a first element
could be termed a second element, and, similarly, a second element
could be termed a first element, without departing from the scope
of example embodiments of the present invention. As used herein,
the term "and/or," includes any and all combinations of one or more
of the associated listed items.
It will be understood that when an element is referred to as being
"connected," or "coupled," to another element, it can be directly
connected or coupled to the other element or intervening elements
may be present. In contrast, when an element is referred to as
being "directly connected," or "directly coupled," to another
element, there are no intervening elements present. Other words
used to describe the relationship between elements should be
interpreted in a like fashion (e.g., "between," versus "directly
between," "adjacent," versus "directly adjacent," etc.).
The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
example embodiments of the invention. As used herein, the singular
forms "a," "an," and "the," are intended to include the plural
forms as well, unless the context clearly indicates otherwise. As
used herein, the terms "and/or" and "at least one of" include any
and all combinations of one or more of the associated listed items.
It will be further understood that the terms "comprises,"
"comprising," "includes," and/or "including," when used herein,
specify the presence of stated features, integers, steps,
operations, elements, and/or components, but do not preclude the
presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
It should also be noted that in some alternative implementations,
the functions/acts noted may occur out of the order noted in the
figures. For example, two figures shown in succession may in fact
be executed substantially concurrently or may sometimes be executed
in the reverse order, depending upon the functionality/acts
involved.
Unless otherwise defined, all terms (including technical and
scientific terms) used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which example
embodiments belong. It will be further understood that terms, e.g.,
those defined in commonly used dictionaries, should be interpreted
as having a meaning that is consistent with their meaning in the
context of the relevant art and will not be interpreted in an
idealized or overly formal sense unless expressly so defined
herein.
Portions of the example embodiments and corresponding detailed
description may be presented in terms of software, or algorithms
and symbolic representations of operation on data bits within a
computer memory. These descriptions and representations are the
ones by which those of ordinary skill in the art effectively convey
the substance of their work to others of ordinary skill in the art.
An algorithm, as the term is used here, and as it is used
generally, is conceived to be a self-consistent sequence of steps
leading to a desired result. The steps are those requiring physical
manipulations of physical quantities. Usually, though not
necessarily, these quantities take the form of optical, electrical,
or magnetic signals capable of being stored, transferred, combined,
compared, and otherwise manipulated. It has proven convenient at
times, principally for reasons of common usage, to refer to these
signals as bits, values, elements, symbols, characters, terms,
numbers, or the like.
In the following description, illustrative embodiments may be
described with reference to acts and symbolic representations of
operations (e.g., in the form of flowcharts) that may be
implemented as program modules or functional processes include
routines, programs, objects, components, data structures, etc.,
that perform particular tasks or implement particular abstract data
types and may be implemented using existing hardware at existing
network elements. Such existing hardware may include one or more
Central Processing Units (CPUs), digital signal processors (DSPs),
application-specific-integrated-circuits, field programmable gate
arrays (FPGAs) computers or the like.
Note also that the software implemented aspects of the example
embodiments may be typically encoded on some form of program
storage medium or implemented over some type of transmission
medium. The program storage medium (e.g., non-transitory storage
medium) may be magnetic (e.g., a floppy disk or a hard drive) or
optical (e.g., a compact disk read only memory, or "CD ROM"), and
may be read only or random access. Similarly, the transmission
medium may be twisted wire pairs, coaxial cable, optical fiber, or
some other suitable transmission medium known to the art. The
example embodiments not limited by these aspects of any given
implementation.
It should be borne in mind, however, that all of these and similar
terms are to be associated with the appropriate physical quantities
and are merely convenient labels applied to these quantities.
Unless specifically stated otherwise, or as is apparent from the
discussion, terms such as "processing" or "computing" or
"calculating" or "determining" of "displaying" or the like, refer
to the action and processes of a computer system, or similar
electronic computing device/hardware, that manipulates and
transforms data represented as physical, electronic quantities
within the computer system's registers and memories into other data
similarly represented as physical quantities within the computer
system memories or registers or other such information storage,
transmission or display devices.
Spatially relative terms, such as "beneath", "below", "lower",
"above", "upper", and the like, may be used herein for ease of
description to describe one element or feature's relationship to
another element(s) or feature(s) as illustrated in the figures. It
will be understood that the spatially relative terms are intended
to encompass different orientations of the device in use or
operation in addition to the orientation depicted in the figures.
For example, if the device in the figures is turned over, elements
described as "below" or "beneath" other elements or features would
then be oriented "above" the other elements or features. Thus, term
such as "below" can encompass both an orientation of above and
below. The device may be otherwise oriented (rotated 90 degrees or
at other orientations) and the spatially relative descriptors used
herein are interpreted accordingly.
Although the terms first, second, etc. may be used herein to
describe various elements, components, regions, layers and/or
sections, it should be understood that these elements, components,
regions, layers and/or sections should not be limited by these
terms. These terms are used only to distinguish one element,
component, region, layer, or section from another region, layer, or
section. Thus, a first element, component, region, layer, or
section discussed below could be termed a second element,
component, region, layer, or section without departing from the
teachings of the present invention.
A method is proposed, in at least one embodiment, for producing a
noise-reduced CT mixed image data record as a result image data
record which comprises the method steps indicated in the following
enumeration:
Simultaneous recording of several energy spectrum-specific CT image
data records X.sub.i with different X-ray energy spectra R.sub.i or
received from several simultaneously recorded energy
spectrum-specific CT image data records X.sub.i with different
X-ray energy spectra R.sub.i,
Calculation of several linear-mixed mixed image data records
.times. ##EQU00007## from the energy spectrum-specific CT image
data records X.sub.i
Frequency band breakdown of the mixed image data records M.sub.m
into a first lowest frequency band, produced with a low-pass filter
F.sub.0, and several higher frequency bands, produced by other
filters F.sub.j, wherein all the other filters F.sub.j block the
frequency zero and the sum
.times..function. ##EQU00008## over all the filters is standardized
for all frequencies f, and
Calculation of a result image data record
.times..function. ##EQU00009## in that each mixed image data record
M.sub.m is multiplied by precisely one filter and with a
location-dependent function g.sub.j,m(r) and thereby totaled,
wherein g.sub.0,0(r)=1.
The inventor has recognized the following:
It is possible to produce, from several energy spectrum-specific CT
image data records X.sub.i, based on different X-ray energy spectra
R.sub.i, several different mixed images according to
.times. ##EQU00010## and to carry out a frequency band breakdown on
these mixed images. In this situation, the first frequency band
corresponds to a low-pass filter F.sub.0, which contains the
frequency f=0 in full strength. The other filters F.sub.j(f) are
designed in such a way that
.times..function. ##EQU00011## for all frequencies. This means that
all the other filters block the frequency. It is now possible to
form the sum over m mixed images with
.times. ##EQU00012## wherein on each mixed image M.sub.m the
operator F.sub.j is applied, and the mixed images differ from one
another at least in one coefficient C.sub.i,m.
On the assumption that locally only two different materials are
present which are mingled microscopically or macroscopically, it is
now possible to define functions g.sub.j,m(r), which ensure that at
the location r a CT image data record is produced, which, apart
from the noise, is identical to the original mixed image M.sub.0.
The following applies accordingly:
.apprxeq..times..function. ##EQU00013## wherein g.sub.0,0(r)=1.
This method is useful in particular when the CT image data record
M.sub.0 exhibits a relatively high noise in comparison with a
noise-optimized mixed image, and, as well as this, the same
high-frequency structures are visible in both images, wherein they
differ from one another only in their amplitude. In order to avoid
discontinuities from occurring in the image by way of the functions
g.sub.j,m(r), care must be taken to ensure that the values of the
scaling functions g.sub.j,m(r) do not vary too much spatially.
In accordance with this recognition, the inventor proposes a method
for producing a noise-reduced CT mixed image data record as a
result image data record which comprises the method steps indicated
in the following enumeration:
Simultaneous recording of several energy spectrum-specific CT image
data records X.sub.i with different X-ray energy spectra R.sub.i or
received from several simultaneously recorded energy
spectrum-specific CT image data records X.sub.i with different
X-ray energy spectra R.sub.i,
Calculation of several linear-mixed mixed image data records
.times. ##EQU00014## from the energy spectrum-specific CT image
data records X.sub.i
Frequency band breakdown of the mixed image data records M.sub.m
into a first lowest frequency band, produced with a low-pass filter
F.sub.0, and several higher frequency bands, produced by other
filters F.sub.j, wherein all the other filters F.sub.j block the
frequency zero and the sum
.times..function. ##EQU00015## over all the filters is standardized
for all frequencies f, and
Calculation of a result image data record
.times..function. ##EQU00016## in that each mixed image data record
M.sub.m is multiplied by precisely one filter F.sub.j and with a
location-dependent function g.sub.j,m(r) and thereby totaled,
wherein g.sub.0,0(r)=1.
Attention is drawn to the fact that, in the examples given here of
the nomenclature and formulae, the counting of the indices begins
in each case at 0, and the formulae given represent only examples
of calculations.
With such a method, a noise reduction is now possible, with which
the edges are approximately retained, wherein the image quality is
potentially better than with non-linear methods, which assess the
local geometry.
In an embodiment of the method according to the invention, it is
proposed that the location-dependent function g.sub.j,m(r) is
formulated in such a way that the local areas of the skin surface
exhibit a different constant value than the inner regions of the
patient.
As an alternative, it is also possible to determine the
location-dependent function g.sub.j,m(r) locally from a statistical
evaluation of the surroundings of each voxel V(r) at the location
r. This can be done to advantage in that:
A CT image data record X.sub.1 is selected,
From this CT image data record X.sub.1 moving via predefined
adjacent voxels V(r.+-..DELTA.r) of each voxel considered V(r) to
the remaining CT image data records X.sub.i, regression
coefficients k.sub.i (=gradient of the regression lines) are
calculated, which reveal the mutual dependency of the CT values of
the adjacent voxels in each case of the CT image data records
X.sub.i to the selected CT image data record X.sub.1,
A location-dependent scaling function
.function..times..times..times..times. ##EQU00017## is
determined,
From this, in turn, the location-dependent function
g.sub.j,m(r)=w.sub.j,m(r)h.sub.m(r) is determined, wherein
.times. ##EQU00018## for all j, and
The result image data record is determined as the summation via the
product from the location-dependent function with the filters and
the mixed images to give
.times..function. ##EQU00019##
As the outcome, this corresponds to a different weighting of the
mixed image data records used, wherein this weighting can also be
carried out by the user of the method as required, in an adjustable
manner, such that, for example, a homogenous noise impression is
produced. In this situation, the scaling h can lead to the result
image E fluctuating sharply in noise without a location-dependent
w.
According to another embodiment variant of the method presented,
the location-dependent function g.sub.j,m(r) can be determined by a
location-dependent classification on the basis of the local CT
values of the voxels. As an alternative, the location-dependent
function g.sub.j,m(r) can also be determined by a classification of
locally-determined materials, wherein the local materials are
determined for preference by an inherently known method of material
breakdown of CT image data records X.sub.i into at least two
materials. In this respect, reference is made, by way of example,
to the Patent Applications under the File References
DE102008018245.1 and DE102005049586.9, the entire contents of each
of which are incorporated herein by reference.
The energy spectrum-specific CT image data records X.sub.i can, for
the method described here, be both two-dimensional sectional image
data records as well as three-dimensional volume image data
records.
For particular preference, two CT image data records X.sub.i of a
dual-energy CT scan can be used as energy-specific CT image data
records X.sub.i.
The CT image data records X.sub.i can in each case derive directly
from scanning with a mono-energy X-ray spectrum, or they can be
calculated by image-based or raw data-based methods, making use of
polychromatic spectra mixed image data records X.sub.i, which in
each case correspond to a scanning with a mono-energy X-ray
spectrum.
As well as the method according to embodiments of the invention,
the inventors also propose a computer system, which comprises a
memory for the storing of a computer program to be carried out
during operation, wherein the computer program carries out the
method steps in accordance with one of the preceding method
embodiments.
In addition to this, an embodiment of the invention also includes a
CT system for the production of several linear mixed image data
records, mixed from the energy spectrum-specific CT image data
records, with a computer system such as described heretofore.
FIG. 1 shows, by way of example, a dual-source/dual-energy CT
system 1, with which the method according to an embodiment of the
invention is carried out. The CT system 1 comprises a first
radiator/detector system with an X-ray tube 2, and a detector 3
located opposite, wherein, with the first radiator/detector system
2, 3 absorption data items from a first X-ray energy spectrum R1
are recorded. The CT system 1 further comprises a second
radiator/detector system, offset by 90.degree., for simultaneous
scanning with a second X-ray energy spectrum R2, consisting of a
second X-ray tube 4, with a second detector 5 located opposite.
Both radiator/detector systems are located on a gantry, which is
arranged in a gantry housing 6 and rotates about a system axis 9
during the scanning.
The patient 7 to be scanned is positioned on a slidable examination
couch 8, which is pushed along the system axis 9 through the
scanning field located in the gantry housing 6. In this situation,
the weakening of X-ray radiation emitted by the X-ray tubes is
measured by the detectors located opposite, and then, on the basis
of the detector data acquired simultaneously by these
radiator/detector systems, CT image data records Xi of the scanned
patient 7 are reconstructed from different X-ray spectra. As a
supplement, the patient 7 can also be injected, with the aid of a
contrast medium applicator 11, even during the scanning, with a
contrast medium bolus, such that, for example, blood vessels become
better identifiable. Furthermore, for cardio images, the cardiac
activity is also measured with the aid of an ECG lead 13, and an
ECG-actuated or triggered scanning is carried out.
The control of the CT system is effected with the aid of a control
and calculation unit 10 via a control and data line 12, by which
the raw data from the detectors 3 and 5 is transformed into control
commands. Located in the memory 14 of the control and calculation
unit 10 are computer programs 15, which, as well as the control of
the CT system 1 and the reconstructions of the CT image data
records, can also carry out the method according embodiments of the
invention.
By way of supplement, it is pointed out that the method can also be
carried out on a computer system which stands separately from the
CT system, as soon as this computer system has been provided with
the corresponding CT image data records or also the raw data for
the independent reconstruction of the CT image data records.
Taking as a basis CT image data records which are produced with the
dual-energy CT system 1 described in FIG. 1, or another
inherently-known design of a CT system, such as a single-source
CT-system with energy-releasing detector, which produces two CT
image data records on the basis of different X-ray energies, it is
possible, for example, for mixed images M0 to be calculated,
with:
.times. ##EQU00020##
As a rule, the image M0 is calculated in order to fulfill a special
diagnostic purpose, such as the subtraction of contrast agent from
the image.
In order to remove the noise from the image M0, typically, by way
of filter operators F0 and F1 a breakdown into two frequency bands
is carried out, wherein F0 designates a low-pass filter and F1
designates a high-pass filter.
The mixed image
.times..times. ##EQU00021## can in this situation be determined,
for example, such that it is the mixed image with the lowest noise,
on the condition that c0,1=0 and
.times. ##EQU00022## This corresponds to a standard CT image, in
which air lies at -1000 HU, water at 0 HU, and which has the lowest
noise. Naturally, other mixed images M1 can also be used, as long
as this allows for a noise reduction to be achieved in the final
result.
It is now possible to eliminate noise from the image M1 if it is
known how the image contrasts in the CT image data records Xi are
correlated with one another. Since it can be assumed locally that
in each case only two materials of constant density and composition
mix with one another, it is known that the CT image data records Xi
are correlated in the surroundings of a point r, and
X.sub.i(r).apprxeq.k.sub.iX.sub.1(r)+t.sub.i, applies, with k1=1
and t1=0, wherein ki represents the correlation coefficients, i.e.
the gradient of the regression lines.
It is therefore possible to determine the coefficients ki, for
example by a linear regression of the CT values in the image data
record X1 and the image data record Xi in a vicinity of the point
r. In principle it is also possible to use other criteria, such as,
for example:
a--A classification on the basis of the CT values in an image data
record, e.g. M0, wherein, if the CT values of the voxels are in the
vicinity of a voxel being observed .rarw.500 HU, in other words if
they define air, then all ki are set to be equal to 1, and
otherwise there applies: ki=ki, 0 with ki, 0=constant.
b--A classification on the basis of known materials in the vicinity
(e.g. from the recognition of a material breakdown of the
dual-energy CT image data record present), wherein ki=ki,B with
ki,B=constant, if the adjacent voxels indicate the presence of
bones and ki=ki,I with ki,I I=constant, if iodine is in the
vicinity.
In regions in which a linear regression does not provide any
reliable results, i.e. with a low correlations coefficient, the ki
can be calculated by a suitable interpolation of the adjacent
voxel.
It is then known that in the frequency band F1 the images M0 and M1
differ locally only by the factor
.function..times..times..times..times. ##EQU00023## There
accordingly applies:
[F.sub.1M.sub.0](r).apprxeq.[F.sub.1M.sub.1](r).times.g.sub.1(r)-
.
The following can therefore be written:
M.sub.0.apprxeq.[F.sub.0M.sub.0](r)+w(r)[F.sub.1M.sub.0](r)+(1-w(r))[F.su-
b.1M.sub.1](r)g.sub.1(r), wherein the weight w(r) is set in such a
way that a special noise impression is produced, e.g. approximately
constant noise everywhere in the image. As an alternative, w=0 can
be selected, such that the upper frequency band derives only from
the image M1. Accordingly, a breakdown into more than two frequency
bands is also possible.
The CT image data records Xi can also be "mono-energetic" image
data records, i.e. CT images with which attempts are made, on the
basis of the multi-energy CT measured data, image-based or raw
data-based, to achieve the image impression of a CT image which was
recorded with only a single photon energy. Corresponding methods
are generally known. As well as this, it is also possible, on the
CT image data records Xi for a beam hardness increase correction,
iterative, for example, to have already taken place.
For a better understanding of the correlation consideration, shown
in FIG. 2 are two diagrammatically-represented CT image data
records X1 and X2, including in each case a plurality of cubic
voxels. A V(r) voxel considered in each case is marked in both CT
image data records X1 and X2 by cross-hatching, wherein the voxel
V(r.+-..DELTA.r) which at least at certain points is immediately
adjacent, is provided with diagonal hatching. For the correlation
calculation in the form of a regression analysis and determination
of the gradient of the regression line as correlation coefficient
ki, the spatially identical voxels of both the CT image data
records are referred to in each case. This is indicated in the
representation by the broken connecting lines between three voxels
in each case.
Although the representation shown here represents only a section
plane in the CT image data records and their spatial correlation,
this two-dimensional consideration can also be extended to a third
dimension, perpendicular to the image plane.
A diagrammatic representation of the method according to an
embodiment of the invention is shown, for example, in FIG. 3. On
the basis of this, several CT image data records Xi are produced
with a M(ulti)-E(nergy) C(omputer) T(omography system). From this,
mixed image data records
.times. ##EQU00024## are formed, which are then broken down, by the
use of different filter operators Fj in each case into different
frequency bands. Finally, a result image E is calculated, in that
mixed image data records F.sub.jM.sub.m, broken down into frequency
bands, are multiplied and totaled, with the use of a
location-dependent function g.sub.j,m(r) with
.times..function. ##EQU00025## wherein g.sub.0,0(r)=1.
A corresponding method diagram is shown in FIG. 4. In the method
step S1, the CT image data records Xi are determined, from which,
in the method step S2, mixed image data records with
.times. ##EQU00026## are formed. This is followed in method step S3
by the breakdown of the mixed image data records into different
frequency bands with F.sub.jM.sub.m. In addition, in an independent
method step S4, from correlation considerations, threshold value
considerations, or findings from a material breakdown with the aid
of the CT image data records Xi or mixed image data records Mm, the
location-dependent function g.sub.j,m(r) is determined in such a
way that, in the method step S5, by weighted totaling of the mixed
images broken down into frequency bands with the location-dependent
function, a result image according to
.times..function. ##EQU00027## is calculated.
Overall, therefore, with an embodiment of the invention a method is
proposed for the production of a noise-reduced CT image data record
by frequency band breakdown, a computer system for carrying out the
method, and a CT system with such a computer system, wherein, from
several simultaneously-recorded energy spectrum-specific CT image
data records X.sub.i several linear-combined mixed image data
records
.times. ##EQU00028## are produced, a frequency band breakdown of
the mixed image data records M.sub.m into a first lowest frequency
band F.sub.0 and several higher frequency bands takes place, and a
result image data record
.times..function. ##EQU00029## is calculated, in that each mixed
image data record M.sub.m is multiplied by precisely one filter and
one location-dependent function g.sub.j,m(r) and totaled, wherein
g.sub.0,0(r)=1.
Although the invention has been illustrated and described in
greater detail by the example embodiment, the invention is not
restricted by the examples disclosed, and other variations can be
derived from these by a person skilled in the art, without
departing from the scope of protection of the invention.
The patent claims filed with the application are formulation
proposals without prejudice for obtaining more extensive patent
protection. The applicant reserves the right to claim even further
combinations of features previously disclosed only in the
description and/or drawings.
The example embodiment or each example embodiment should not be
understood as a restriction of the invention. Rather, numerous
variations and modifications are possible in the context of the
present disclosure, in particular those variants and combinations
which can be inferred by the person skilled in the art with regard
to achieving the object for example by combination or modification
of individual features or elements or method steps that are
described in connection with the general or specific part of the
description and are contained in the claims and/or the drawings,
and, by way of combinable features, lead to a new subject matter or
to new method steps or sequences of method steps, including insofar
as they concern production, testing and operating methods.
References back that are used in dependent claims indicate the
further embodiment of the subject matter of the main claim by way
of the features of the respective dependent claim; they should not
be understood as dispensing with obtaining independent protection
of the subject matter for the combinations of features in the
referred-back dependent claims. Furthermore, with regard to
interpreting the claims, where a feature is concretized in more
specific detail in a subordinate claim, it should be assumed that
such a restriction is not present in the respective preceding
claims.
Since the subject matter of the dependent claims in relation to the
prior art on the priority date may form separate and independent
inventions, the applicant reserves the right to make them the
subject matter of independent claims or divisional declarations.
They may furthermore also contain independent inventions which have
a configuration that is independent of the subject matters of the
preceding dependent claims.
Further, elements and/or features of different example embodiments
may be combined with each other and/or substituted for each other
within the scope of this disclosure and appended claims.
Still further, any one of the above-described and other example
features of the present invention may be embodied in the form of an
apparatus, method, system, computer program, tangible computer
readable medium and tangible computer program product. For example,
of the aforementioned methods may be embodied in the form of a
system or device, including, but not limited to, any of the
structure for performing the methodology illustrated in the
drawings.
Even further, any of the aforementioned methods may be embodied in
the form of a program. The program may be stored on a tangible
computer readable medium and is adapted to perform any one of the
aforementioned methods when run on a computer device (a device
including a processor). Thus, the tangible storage medium or
tangible computer readable medium, is adapted to store information
and is adapted to interact with a data processing facility or
computer device to execute the program of any of the above
mentioned embodiments and/or to perform the method of any of the
above mentioned embodiments.
The tangible computer readable medium or tangible storage medium
may be a built-in medium installed inside a computer device main
body or a removable tangible medium arranged so that it can be
separated from the computer device main body. Examples of the
built-in tangible medium include, but are not limited to,
rewriteable non-volatile memories, such as ROMs and flash memories,
and hard disks. Examples of the removable tangible medium include,
but are not limited to, optical storage media such as CD-ROMs and
DVDs; magneto-optical storage media, such as MOs; magnetism storage
media, including but not limited to floppy disks (trademark),
cassette tapes, and removable hard disks; media with a built-in
rewriteable non-volatile memory, including but not limited to
memory cards; and media with a built-in ROM, including but not
limited to ROM cassettes; etc. Furthermore, various information
regarding stored images, for example, property information, may be
stored in any other form, or it may be provided in other ways.
Example embodiments being thus described, it will be obvious that
the same may be varied in many ways. Such variations are not to be
regarded as a departure from the spirit and scope of the present
invention, and all such modifications as would be obvious to one
skilled in the art are intended to be included within the scope of
the following claims.
* * * * *